Data security supervision method for public data operation platform

By using machine learning-based sensitive data automatic identification algorithm and dynamic desensitization technology on the public data operation platform, combined with the desensitization abnormality detection model, the problems of insufficient protection intensity and task failure during data desensitization are solved, and efficient and accurate sensitive data protection and stability and security are achieved.

CN119885281AActive Publication Date: 2025-04-25CHANGSHA DIGITAL GROUP CO LTD
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Patent Information

Application Number
CN202510355687.9
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-03-25
Publication Date
2025-04-25
Estimated Expiration
2045-03-25

AI Technical Summary

Technical Problem

The existing data security management technology has problems such as incompleteness, abnormal distribution, insufficient algorithm design during data desensitization, resulting in insufficient protection intensity or failure of business logic. System computing resource limitations and transmission interruptions may lead to failure of desensitization tasks or exposure of sensitive data.

Method used

The sensitive data automatic identification algorithm based on machine learning is used to scan the data sets of the public data operation platform, accurately locate sensitive data, and dynamically adapt the desensitization technology based on data sensitivity and business attributes. By obtaining extreme distribution information of desensitization data, unbalanced desensitization intensity and data transmission link interrupt information, a desensitization abnormality detection model is built to monitor the desensitization process in real time and automatically trigger the recovery mechanism.

Benefits of technology

It realizes efficient and accurate identification and protection of sensitive data in public data operation platforms, ensures that the data meets privacy protection requirements during the sharing process, avoids the risk of data leakage or privacy violations in desensitization operations, and ensures the stability and security of desensitization tasks.

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Abstract

The invention discloses a data security supervision method for a public data operation platform, particularly relates to the technical field of data security supervision, and can accurately position sensitive information in a large-scale data set through a sensitive data automatic identification algorithm based on machine learning. The sensitive data are classified according to the sensitivity and the service attributes, the most suitable desensitization technology can be adopted according to the sensitive data of different types, the desensitization intensity and technology can be automatically adjusted according to the sensitivity of the data, and flexible privacy protection is achieved. Potential abnormities in the data desensitization process are deeply analyzed by obtaining extreme distribution information, desensitization intensity imbalance information and data transmission link interruption information of desensitization data, and problems in desensitization task execution are recognized in time, so that the data leakage risk or privacy infringement in desensitization operation is avoided.
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Citation Information

Patent Citations

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  • Archive management method and system based on big data

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  • Dynamic desensitization method and system for intermediate layer data stream

    CN118734365A

  • E-commerce platform information security desensitization scheme analysis system based on artificial intelligence

    CN119538316A

  • Method and system for processing medical data

    US20230094564A1

Cited By

  • Safety supervision method and system for public data operation platform

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